1. Field of the Disclosure
This invention relates to a method of simulating engine operation, and particularly to creating a simplified engine model.
2. Background Art
A range of modelling approaches is known for simulating engine operation. These are used, for example, in the development and testing of control strategies for engines. In many cases, due to their simplicity, modelling approaches enable simulation results to be obtained quickly. However, the results obtained are inaccurate due to the degree of approximation used.
A more complex known modelling technique is crank-resolved modelling. In crank resolved models, the cylinders of an engine are divided into sections. The propagation effects along the cylinders are then analysed. In crank resolved simulations, full partial differential equations are solved in order to capture wave-action effects in an engine. This approach to modelling is accurate as it looks at engine characteristics, and takes into account individual in-cycle events. However, due to the complexity of the computations involved, it is not possible to obtain simulation results on a real-time basis using known crank-resolved modelling techniques.
Mean value modelling is another known technique used in engine operation simulation. This approach uses calibration data obtained from tests run on engine test beds. The calibration data is used to approximate the behaviour of some or all of the components of an engine during a simulated engine cycle. Mean value modelling is useful because is it can produce real-time results in a simulation cycle. However, mean value modelling is only capable of representing the output effects of engine behaviour. Mean value models do not simulate for example angle-by-angle variation of simulation quantities that can be used for modern control algorithms. Nor do they attempt to capture wave-action effects caused by pressure propagating along pipes in an engine. It will be appreciated by the skilled person that wave effects should preferably be considered to model tuning of an engine, as this enables the user to size engine components and optimise performance.
A number of modelling packages are known which aim to combine the known modelling approaches to produce an engine model which outputs accurate results in real time. For Example, SimuQuest has produced a real-time crank resolved simulation model, Enginuity. This simulation model is capable of integrating other vehicle components with an engine model to produce real-time simulation results. However, all components outside the combustion chamber in the Enginuity model are represented by mean value models. The results output are therefore based on approximations for most of the vehicle, which compromises the accuracy of the results obtained from the simulation.
A problem which remains with existing modelling techniques is the inability to model in-cycle engine events to produce accurate simulation results on a real-time basis. Instead, current methods focus on increasing the complexity of crank resolved models, making them less suitable for producing real-time simulation results, and then relying on approximated control-based models in real-time simulations.